Urban Environment Research Articles

Quantitative assessment and driving factors analysis of surface urban heat island of urban agglomerations in China based on GEE.

The urban heat island (UHI) effect generated by the development of high-speed urbanization has become one of the major problems affecting the urban ecological environment. As the main body of urbanization in China, China's urban agglomerations are the core areas of urban heat island effect. The purpose of this study is to study the spatial-temporal characteristics and driving factors of surface urban heat island in 19 urban agglomerations in China, with a view to providing theoretical references for the prevention of urban thermal environmental risks. Based on Google Earth Engine (GEE), this paper estimated the surface urban heat island intensity (SUHII) of 19 urban agglomerations in China from 2003 to 2019 using MODIS land surface temperature (LST) data. Correlation analysis and regression analysis were used to explore the correlation between the change of SUHII and driving factors. Finally, the driving factors of SUHII were detected by the geo-detector model. Results showed that (1) the SUHII of 19 urban agglomerations in arid and semi-arid areas of northwestern China is higher than that in humid areas of eastern and southeastern China. (2) The SUHII of 19 urban agglomerations in China generally shows a decreasing trend, and the spatial variation of the change trend is significant. (3) There are positive correlations between SUHII and reference evapotranspiration (ET0), population density (POP), gross domestic product (GDP), nitrogen dioxide (NO2), ozone (O3), and ultraviolet aerosol index (UVAI); negative correlations with normalized difference vegetation index (NDVI), DEM, sulfur dioxide (SO2), carbon monoxide (CO), and formaldehyde (HCHO); the correlations all pass the significance test of P < 0.05 and are statistically significant. (4) The factor detection results showed that NDVI, land cover type (LC), and UVAI were the main driving factors of SUHII. The interaction detection results showed that the interaction between O3 and UVAI had the most significant impact on SUHII.

GC-YOLOv9: Innovative smart city traffic monitoring solution

In urban smart city environments, traffic hazards can lead to catastrophic outcomes, including significant property losses and severe threats to public safety. Conventional traffic monitoring systems are limited in terms of accuracy and speed, presenting significant challenges for real-time traffic surveillance. To tackle these challenges, this paper introduces the GC-YOLOv9 algorithm. Specifically, we have enhanced the YOLOv9 model by incorporating Ghost Convolution, markedly improving the model’s perceptual abilities and detection accuracy. Furthermore, this study designed an integrated smart city framework that includes layers for service applications, the Internet of Things, edge processing, and data centers. By deploying the enhanced YOLOv9 model within this framework, our method achieved mAP@0.5 scores of 77.15 and 74.95 on the BDD100K and Cityscapes datasets, respectively, surpassing existing technologies. Additionally, the potential applications of this method in public area fire safety management, forest fire monitoring, and intelligent security systems further underscore its significant value in improving the safety and efficiency of smart cities.

Moving Beyond Clinical Imaginaries: Technogeographies of the Everyday Urban.

In this paper, we analyse the intersections between care and place in mundane spaces not explicitly designed for the provision of care, and where digital technologies are used to mediate ecologies of distress in the city. We locate our analysis alongside studies of how digital technologies impact the experience of care within non-clinical spaces, whilst noting that much research on the use of technologies for care remains haunted by clinical imaginaries. Bringing together ideas of multi-sited therapeutic assemblages, technogeographies of care, and how places-by-proxy can act as conduits for care, we explore an example of an online app being used in public space to manage experiences of anxiety in an everyday urban environment. We reflect on this illustrative example to trace the movement of care as it is mediated through digital technologies-out of the clinic, beyond the home, and into the ordinary spaces of the city. We conclude that the entanglements of digital technologies and ordinary urban places prompt us to entirely reconsider questions of the where of care.

Species Diversity of Anastrepha Fruit Flies (Diptera: Tephritidae) in Environments with Different Levels of Anthropogenic Changes.

Studies on the diversity of Anastrepha species have been conducted mainly in agricultural orchards due to the economic importance of this insect group, consequently, research on fruit flies in undisturbed environments is scarce. Moreover, very few studies have investigated the diversity of fruit flies in urban areas, where fruit flies survive under native or exotic hosts. Thus, to understand the diversity of Anastrepha species in an environment with different anthropization degrees, surveys were carried out in four areas of the "Luiz de Queiroz" campus, in Piracicaba, São Paulo State (Brazil), using Multilure traps with putrescine and ammonium acetate for 12 months. The software R 3.6.3 was used to characterize the fruit fly community and the faunistic analysis was carried out using the ANAFAU program. The analysis of species richness and total abundance of fruit flies among the sites was carried out using the rarefaction method and adjustment to the generalized linear model (GLM) using the Poisson distribution, respectively. We collected 1,080 females and 14 species of Anastrepha in the four sampled sites. Anastrepha fraterculus and A. obliqua were the predominant species (behavioral patterns). Similar to agricultural sites, A. fraterculus and A. obliqua also show a predominant occurrence in urban environments.

Networked everyday lives in the ‘care-full’ city: A framework for examining the complexities of immigrants living with dementia, carepartners, and care workers

ABSTRACT The ways in which people living with dementia (PLWD) care and are cared for in urban and suburban environments is not fully understood. Specifically, there is limited research on the impact neighborhoods have on the intersectional experiences of well-being for PLWD and their formal and informal caregivers—particularly for immigrants, women, and those living in under-resourced suburban areas. Writing from the geographical context of the inner suburb of Scarborough in Toronto, Canada, we present a framework for understanding the everyday complexities of care practices in this triad of individuals—PLWDs, care partners, and care workers—that considers their diverse practices, contexts, identities, and relations through time. Documenting these networks of caring complexities, represented in social and spatial ways, can disrupt the ways in which neoliberalism has relegated the understanding of care to be a highly gendered and racialized problem, as well as an individual problem to be solved by the free market, and to be contained in the home between family members (not in the public community realm).

Effect of Urban Environment on Cardiovascular Health: A Feasibility Pilot Study using Machine Learning to Predict Heart Rate Variability in Heart Failure Patients

Effect of Urban Environment on Cardiovascular Health: A Feasibility Pilot Study using Machine Learning to Predict Heart Rate Variability in Heart Failure Patients

Effects of urban streams on muscle non-protein thiols, gill and liver histopathology in zebrafish (Danio rerio) assessed by active biomonitoring

Aquatic biota are exposed to toxic substances resulting from human activities, reducing environmental quality and can compromise the health of the organisms. This study aimed to employ Danio rerio as an environmental bioindicator, analyzing the effects of water from distinct urban aquatic environments. An active biomonitoring system was set up to compare the temporal dynamics of histological biomarkers for gill and liver and the patterns of non-protein thiols (NPSH) in muscle in specimens exposed for 3, 6, and 12 days. Three large urban basins in the city of Campo Grande (Midwest of Brazil) were selected. Two sites are in a very populous area (i.e Lagoa and Bandeira) and another on in an area with agricultural activities (i.e Anhanduí). All the streams displayed distinct qualitative characteristics. The presence of metals, including Mn, Zn, Fe, and Al, as well as pH, temperature, and dissolved oxygen, accounted for 38% of the variability (PC1), while total solids, conductivity, ammonia, nitrite, and explained 24 % (PC2). Degree tissue changes index (DTC) in gill and the concentration of NPSH increased in all streams during 3, 6 and 12 days of exposure. DTC in liver increases in all exposure times in most populous stream (i.e Lagoa and Bandeira). Histopathological evidence in the gill, including proliferation, desquamation, and necrosis of the primary lamellar epithelium; fusion and aneurysms in the secondary lamellar epithelium were observed after three days of exposure. Degenerative nuclear figures were noted in the liver after three days of exposure, followed by hepatocellular hypertrophy, lipidosis, and necrosis at twelve days. Our findings showing time-dependent effects of urban aquatic environments in histopathological (i.e DTC) and biochemical biomarkers in zebrafish. The biomonitoring model enabled a comparison of the temporal dynamics of various health markers, using zebrafish as bioindicator. Future studies might use this experimental model and biomarkers for environmental biomonitoring program.

Firefighting Vehicle Dispatch and Route Planning Model Based on Priority Passage Rights

&lt;div&gt;Efficient fire rescue operations in urban environments are critical for saving lives and reducing property damage. By utilizing connected vehicle systems (CVS) for firefighting vehicles planning, we can reduce the response time to fires while lowering the operational costs of fire stations. This research presents an innovative nonlinear mixed-integer programming model to enhance fire rescue operations in urban settings. The model focuses on expediting the movement of firefighting vehicles within intricate traffic networks, effectively tackling the complexities associated with collaborative dispatch decisions and optimal path planning for multiple response units. This method is validated using a small-scale traffic network, providing foundational insights into parameter impacts. A case study in Sioux Falls shows its superiority over traditional “nearest dispatch” methods, optimizing both cost and response time significantly. Sensitivity analyses involving clearance speed, clearance time, minimum rescue force, and fire loss parameters contribute to the enhancement of urban fire rescue operations and the refinement of practical decision support systems.&lt;/div&gt;

Reviving the past: urban strategies for renovating historic commercial streets in city centers

Historical city centers are one of the reasons that give cities their identity, memory, and sense of belonging. The commercial areas within these centers are particularly important, as they contribute significantly to the vitality of the urban environment. However, due to rapid developments in recent times, many of these historic commercial streets have lost their significance and fallen victim to informal usage, resulting in the erosion of their historic identity. Consequently, it becomes imperative to renovate these historic commercial streets to preserve the community’s identity. The proposed methodology aims to foster local culture by revitalizing these streets and emphasizing the principles and criteria of heritage preservation that not only preserve the community’s identity but also serve as vibrant and inclusive spaces for residents and visitors alike to fulfill the concept of vitality and livability. In this context, the focus is on protecting historical areas and ensuring their ongoing relevance and benefits, extending not only to street users but also to the entire community. To achieve this, a series of steps are suggested for the renovation of historic commercial streets within city centers, accompanied by a reliable set of criteria that preserve their visual identity rooted in history. To demonstrate the application of these criteria, a case study was conducted for the proposed renovation of Mahmud Al-Banna Street, a historic commercial street in downtown Tanta, Egypt. The objective of the study was to develop strategies that would effectively address various aspects, including urban, visual, environmental, and economic issues. As a result, the research concluded that the proposed regeneration strategies, if implemented, could enhance the vitality and livability of the historic commercial districts for other urban environments.

Understanding the Dynamics of Source-Apportioned Black Carbon in an Urban Background Environment

Understanding the Dynamics of Source-Apportioned Black Carbon in an Urban Background Environment

Recent Developments in AI and ML for IoT: A Systematic Literature Review on LoRaWAN Energy Efficiency and Performance Optimization.

The field of the Internet of Things (IoT) is dominating various areas of technology. As the number of devices has increased, there is a need for efficient communication with low resource consumption and energy efficiency. Low Power Wide Area Networks (LPWANs) have emerged as a transformative technology for the IoT as they provide long-range communication capabilities with low power consumption. Among the various LPWAN technologies, Long Range Wide Area Networks (LoRaWAN) are widely adopted due to their open standard architecture, which supports secure, bi-directional communication and is particularly effective in outdoor and complex urban environments. This technology is helpful in enabling a variety of IoT applications that require wide coverage and long battery life, such as smart cities, industrial IoT, and environmental monitoring. The integration of Machine Leaning (ML) and Artificial Intelligence (AI) into LoRaWAN operations has further enhanced its capability and particularly optimized resource allocation and energy efficiency. This systematic literature review provides a comprehensive examination of the integration of ML and AI technologies in the optimization of LPWANs, with a specific focus on LoRaWAN. This review follows the PRISMA model and systematically synthesizes current research to highlight how ML and AI enhance operational efficiency, particularly in terms of energy consumption, resource management, and network stability. The SLR aims to review the key methods and techniques that are used in state-of-the-art LoRaWAN to enhance the overall network performance. We identified 25 relevant primary studies. The study provides an analysis of key findings based on research questions on how various LoRaWAN parameters are optimized through advanced ML, DL, and RL techniques to achieve optimized performance.

SEM-EDS-based rapid measurement and size-fractionated speciation of airborne particulate matter and associated metals utilizing plant leaves.

This study was conducted to assess particulate matter pollution and the accumulation of airborne toxic metals by studying the foliar deposition pattern in an urban environment. To this end, two commonly growing plants (Senna siamea (Lam.) H.S.Irwin & Barneby and Alstonia scholaris (L.) R.Br.) from the busiest traffic squares of the city (Nehru Chowk) in Bilaspur, India, were selected for detailed study. For this purpose, plant leaf samples of both plant species were collected from pollution-affected areas and a reference site (unpolluted) in the city and examined by scanning electron microscopy and energy dispersive X-ray spectroscopy (SEM-EDS) to estimate the accumulation of PM-bound toxic metals at the leaf surfaces. The results of this study showed that the leaves of both plants accumulate PM in different size ranges. Although both plant leaves showed accumulation of PM from respirable suspended particulate matter (RSPM) to ultra-fine particles (UFPs: < 0.1: less than 100nm) range along with toxic metals, S. siamea retained a higher level of PM than A. scholaris due to better micro-morphological properties on both leaf surfaces. The size of some PM was found to be smaller than the stoma openings. The EDS study proved the presence of harmful airborne toxic metals (Pb, Cd, Cu, Zr, Al, Co, etc.) in these PMs of ambient air. This indicates that toxic metals can enter the leaves through stomatal openings. The results of this study recommended that both plants can be used as a tool to minimise PM pollution.

The (re)production of health in climate change

To date, health in the context of climate change has mainly been considered from a biomedical perspective, whose pathogenic focus on health risks has primarily promoted curative and/or behavioral problem-solving strategies. This article therefore examines health in climate change from a perspective of Urban Public Health and political science, which has received less attention so far. The aim is to address existing constructions of health in climate change and their implications for dealing with the climate crisis, in particular regarding the design of urban environments. In doing so, it adopts a regulation-theoretical approach that allows for a theoretically grounded analysis of health in climate change, taking the triangle of nature, society and the individual as the object of research and revealing the significance of existing constructions of health—understood as a social relation—and its (re)production in climate change. This theoretical approach is extended to aspects of different spatial forms and the productions of space in social relations. The theoretical foundation makes it possible to recognize that there are understandings of health in climate change discourse that largely exclude the causes of climate change and thus make its treatment selective. As a result, broad socio-ecological transformation processes are obstructed, while the structural causes of climate change are preserved and stabilized despite their crisis character. An understanding of health that also sees health as a resource in a salutogenic sense and that strengthens the promotion of health by means of structural changes is being pushed into background. Positioning climate change as a public health issue requires a shift from curative, individual and behavioral interventions toward a focus on structural health promotion, especially through the development of health-promoting, just and climate-friendly urban environments. It also means that health must once again become more of a political issue and that existing boundaries between the private and public spheres must be questioned.

Analysis of secondary inorganic aerosols over the greater Athens area using the EPISODE–CityChem source dispersion and photochemistry model

Abstract. Secondary inorganic aerosols (SIAs) are major components of fine particulate matter (PM2.5), having substantial implications for climate and air quality in an urban environment. In this study, a state-of-the-art thermodynamic model has been coupled to the source dispersion and photochemistry city-scale chemistry transport model EPISODE–CityChem, which is able to simulate pollutants at a horizontal resolution of 100 m×100 m, to determine the equilibrium between the inorganic gas and aerosol phases over the greater Athens area, Greece, for the year 2019. In agreement with in situ observations, sulfate (SO42-) is calculated to have the highest annual mean surface concentration (2.15 ± 0.88 µg m−3) among SIAs in the model domain, followed by ammonium (NH4+; 0.58 ± 0.14 µg m−3) and fine nitrate (NO3-; 0.24 ± 0.22 µg m−3). Simulations denote that NO3- formation strongly depends on the local nitrogen oxide emissions, along with the ambient temperature, the relative humidity, and the photochemical activity. Additionally, we show that anthropogenic combustion sources may have an important impact on the NO3- formation in an urban area. During the cold period, the combined effect of decreased temperature in the presence of non-sea-salt potassium favors the partitioning of HNO3 in the aerosol phase in the model, raising the NO3- formation in the area. Overall, this work highlights the significance of atmospheric composition and the local meteorological conditions for the equilibrium distribution of nitrogen-containing semi-volatile compounds and the acidity of inorganic aerosols, especially in urban areas where atmospheric trace elements from natural and anthropogenic sources coexist.

Smart Traffic Management: Enhancing Urban Mobility through Predictive Analysis and AI-Driven Solutions

In urban environments, the issue of unauthorized parking in designated no-parking zones persists, leading to traffic congestion and safety hazards. inaccurate license plate recognition, License plate (LP) detection is a crucial task for Automatic License Plate Recognition (ALPR) systems. Most existing LP detection networks can detect License plates, but their accuracy suffers when license plates (LPs) are tilted or deformed due to perspective distortion. This leading to difficulties in identifying vehicle owners. To address this challenge, this project present TraceMe, a predictive system utilizing advanced machine learning algorithms. The system employs YOLOv8 for efficient object detection, focusing on identifying vehicles in no-parking zones, and Tesseract OCR for accurate license plate recognition. The extracted license plate information is then processed by a machine learning model trained to predict the owner of the vehicle. The proposed system involves collecting and annotating a diverse dataset, training YOLOv8 and LPRNet model for vehicle number plate detection, utilizing Tesseract OCR for license plate extraction, and implementing a machine learning model for owner identification. Real-time processing and integration with surveillance systems allow for immediate identification of unauthorized parking incidents. The system generates alerts or notifications, aiding law enforcement in enforcing parking regulations.TraceMe not only provides a technological solution to mitigate unauthorized parking but also contributes to improved traffic management and public safety.

Development of an Intelligent Road-Crossing Sensor System for Enhanced Pedestrian Safety

Pedestrian safety at road crossings in urban environments is a critical issue due to the increasing vehicular traffic and high pedestrian density. Traditional traffic control measures often fail to adequately address the dynamic interactions between vehicles and pedestrians, leading to significant risks of accidents. This study proposes the development of an intelligent road-crossing sensor system leveraging advanced technologies such as sensors, artificial intelligence (AI), and the Internet of Things (IoT). The system aims to enhance pedestrian safety by providing real-time alerts and adaptive traffic control, thereby reducing the risk of pedestrian-vehicle collisions. The methodology includes sensor selection, data collection, machine learning model development, and system implementation and testing. The potential benefits and challenges of deploying such systems are also discussed, offering insights into creating smarter and safer urban environments. Keywords: Pedestrian safety, intelligent sensor systems, road crossing, vehicle detection, traffic signals

Enhanced Strapdown Inertial Navigation System (SINS)/LiDAR Tightly Integrated Simultaneous Localization and Mapping (SLAM) for Urban Structural Feature Weaken Occasions in Vehicular Platform

LiDAR-based simultaneous localization and mapping (SLAM) offer robustness against illumination changes, but the inherent sparsity of LiDAR point clouds poses challenges for continuous tracking and navigation, especially in feature-deprived scenarios. This paper proposes a novel LiDAR/SINS tightly integrated SLAM algorithm designed to address the localization challenges in urban environments characterized in sparse structural features. Firstly, the method extracts edge points from the LiDAR point cloud using a traditional segmentation method and clusters them to form distinctive edge lines. Then, a rotation-invariant feature—line distance—is calculated based on the edge line properties that were inspired by the traditional tightly integrated navigation system. This line distance is utilized as the observation in a Kalman filter that is integrated into a tightly coupled LiDAR/SINS system. This system tracks the same edge lines across multiple frames for filtering and correction instead of tracking points or LiDAR odometry results. Meanwhile, for loop closure, the method modifies the common SCANCONTEXT algorithm by designating all bins that do not reach the maximum height as special loop keys, which reduce false matches. Finally, the experimental validation conducted in urban environments with sparse structural features demonstrated a 17% improvement in positioning accuracy when compared to the conventional point-based methods.

Measurement and Evaluation of the Business Environment in Large and Medium-Sized Cities in China

The comprehensive development level of the business environment reflects the quality of a region’s economic development, and a good business environment will give a city a strong vitality. This paper uses the entropy method to measure and evaluate the business environment of 106 large and medium-sized cities in China from 2017 to 2021. The results show that: From the spatial point of view, the business environment index of China’s cities shows a gradually decreasing pattern from east to west and from south to north. The balance of the business environment of large and medium-sized cities in China is divided into four levels according to the standard deviation of the ranking of each sub-index. The greater the standard deviation, the more unbalanced the overall development of the business environment in the region. Finally, this paper put forward countermeasures and suggestions to further optimize the business environment.

Regulated Pandemic Spaces: Spatial Crises in COVID Comics.

Close-reading sequential comics and cartoons such as He Zhu's "Lockdown," Rivi Handler-Spitz's "Morning Commute," Yang Ji's "Quarantine," and Thi Bui, Will Evans, Sarah Mirk, Amanda Pike, and Esther Kaplan's "In/Vulnerable," this article investigates the networked spatial crises that have emerged during COVID-19. As the global pandemic reshaped social, economic, and cultural landscapes, it is crucial to understand the spatial implications of these transformations. By analyzing graphic medical texts, which serve as visual narratives that capture the lived experiences and perceptions of individuals within these crises, the present essay offers a nuanced exploration of the intricate relationships between space, society, and the effects of the pandemic. The article identifies and examines the various spatial crises that have emerged in the COVID era, such as disrupted urban environments, altered social dynamics, spaces of contamination, contraction of space, and the reconfiguration of workspaces. Drawing on theorists like Michael Foucault and Henri Lefebvre, this essay illustrates how these crisis-induced spatial transformations are represented, experienced, and contested. Ultimately, the article not only contributes to a deeper understanding of the complex interplay between the pandemic and space but also addresses the challenges of our evolving world.

Regulated Pandemic Spaces: Spatial Crises in COVID Comics.

Close-reading sequential comics and cartoons such as He Zhu's "Lockdown," Rivi Handler-Spitz's "Morning Commute," Yang Ji's "Quarantine," and Thi Bui, Will Evans, Sarah Mirk, Amanda Pike, and Esther Kaplan's "In/Vulnerable," this article investigates the networked spatial crises that have emerged during COVID-19. As the global pandemic reshaped social, economic, and cultural landscapes, it is crucial to understand the spatial implications of these transformations. By analyzing graphic medical texts, which serve as visual narratives that capture the lived experiences and perceptions of individuals within these crises, the present essay offers a nuanced exploration of the intricate relationships between space, society, and the effects of the pandemic. The article identifies and examines the various spatial crises that have emerged in the COVID era, such as disrupted urban environments, altered social dynamics, spaces of contamination, contraction of space, and the reconfiguration of workspaces. Drawing on theorists like Michael Foucault and Henri Lefebvre, this essay illustrates how these crisis-induced spatial transformations are represented, experienced, and contested. Ultimately, the article not only contributes to a deeper understanding of the complex interplay between the pandemic and space but also addresses the challenges of our evolving world.